This dataset contains all data and R code, in RMarkdown notebook format, needed to reproduce all statistical analysis, figures, and tables in the manuscript:Jeffers, D., J. S. Smith, E. D. Womack, Q. D. Read, and G. L. Windham. 2024. Comparison of in-field and laboratory-based phenotyping methods for evaluation of aflatoxin accumulation in maize inbred lines. Plant Disease. (citation to be updated upon final acceptance of MS)There is a critical need to quickly and reliably identify corn genotypes that are resistant to accumulating aflatoxin in their kernels. We compared three methods of determining how resistant different corn genotypes are to aflatoxin accumulation: a field-based assay (side-needle inoculation) and two different lab-based assays (wounding and non-wounding kernel screening assays; KSA). In this data object, we present the data from the lab and field assays, statistical models that are fit to the data, procedures for comparing model fit of different variants of the model, and model predictions. This includes how reliably each assay identifies resistant and susceptible check varieties, and how well correlated the assay methods are with one another. Statistical analyses are done using R software, including Bayesian models fit with Stan software.The following files are included:ksa_analysis_revised.Rmd: RMarkdown notebook with all code needed to reproduce analyses and create figures and tables in manuscriptksa_analysis_revised.html: HTML rendered output of notebookstep1_ksa.tsv: tab-separated data file with data from the lab assay. Columns include sample ID, genotype ID and entry code, year, treatment (wound or no-wound), subsample ID, replicate ID, aflatoxin concentration (in units of ng/g), logarithm of aflatoxin concentration, and a column indicating genotypes that are susceptible or resistant checksstep1_ksa_field.tsv: tab-separated data file with data from the field assay. Columns similar to the lab assay data file with an additional column for row in which the sample was planted.ksa_cov_mod.tsv: tab-separated data file with secondary infection covariate data from the lab assay. Columns similar to the lab assay data file with columns for secondary Asp, Fus, and NI infections and their logarithms.brmfits.zip: zip archive with 12 .rds files. These are model output files for the Bayesian mixed effect models presented in the MS that were fitted using the R function brm(). You may download these to reproduce output without having to compile and run the models yourself.The three .tsv data files should be placed in a subdirectory called "data" in the same directory where the .Rmd notebook is located.